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Physics Simulation Python Jobs in Michigan (NOW HIRING)

ROUSH

CAE Analyst II

Livonia, MI · On-site

Connect simulation with practical aspects of Cost/Weight/Investment (CWI), Design for Manufacturing ... D. in Engineering, Physics or Mathematics. * Experience in writing scripts and process automation.

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Physics Simulation Python information

What is a physics simulation Python developer?

A Physics Simulation Python developer is a professional who uses the Python programming language to design, implement, and analyze simulations that model physical systems and phenomena. These simulations can range from simple particle motion to complex fluid dynamics or electromagnetic fields, and are widely used in research, engineering, gaming, and education. The developer typically utilizes scientific libraries such as NumPy, SciPy, and PyBullet, and may also work with visualization tools to present simulation results. Their work helps in understanding real-world physics problems, testing hypotheses, or creating realistic interactive environments.

What are the key skills and qualifications needed to thrive as a physics simulation Python developer?

To excel as a Physics Simulation Python Developer, you need a strong background in physics, mathematics, and proficiency in Python programming, often supported by a degree in physics, engineering, or computer science. Familiarity with simulation libraries (such as NumPy, SciPy, PyBullet, or SimPy), version control systems like Git, and experience with visualization tools are commonly required. Analytical thinking, problem-solving abilities, and effective collaboration are standout soft skills in this role. These skills enable the development of accurate, efficient simulations and foster productive teamwork in research or engineering projects.

What are some common challenges faced by professionals working in physics simulation with Python, and how can they be addressed?

Professionals in Physics Simulation with Python often encounter challenges such as optimizing simulation performance, ensuring numerical accuracy, and integrating complex libraries (e.g., NumPy, SciPy, PyBullet) into larger workflows. Addressing these issues typically involves using efficient coding practices, leveraging vectorized operations, and validating results with analytical solutions or experimental data. Collaboration with domain experts and regular code reviews can also help maintain code reliability and project scalability. Staying updated with the latest simulation frameworks and actively participating in open-source communities are excellent ways to overcome technical hurdles.

What is the difference between Physics Simulation Python vs Mechanical Engineer?

AspectPhysics Simulation PythonMechanical Engineer
Required CredentialsProgramming skills, knowledge of physics, often a degree in physics or computer scienceMechanical engineering degree, professional licensure in some regions
Work EnvironmentSoftware development, research labs, simulation environmentsDesign offices, manufacturing plants, R&D departments
Industry UsageSimulation software development, research, academiaProduct design, manufacturing, systems optimization

Physics Simulation Python focuses on developing and implementing physics-based simulations using Python programming, often in research or software development contexts. Mechanical Engineers apply engineering principles to design, analyze, and manufacture mechanical systems. While both roles require a strong understanding of physics, Physics Simulation Python emphasizes coding and simulation, whereas Mechanical Engineering involves practical design and application in physical systems.

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For Physics Simulation Python jobs in Michigan, the most frequently searched job titles are:

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The top searched job categories for Physics Simulation Python jobs in Michigan are:

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Cities in Michigan with the most Physics Simulation Python job openings:

Physics Simulation Python jobs near you

Automotive Propulsion Software Research Engineer

Lorven Technologies

Warren, MI • On-site

Full-time

Re-posted 24 days ago

Job description

Role: Automotive Propulsion Software Research Engineer
Location: Fully onsite. Warren, MI
Contract role
Job description:
Develop an LLM and agent based assistant to automate simulation setup, run deck generation, boundary condition/mesh recommendations, results review, and requirements alignment across 1D/3D tools (e.g., GT POWER/Simcenter Amesim, ANSYS/STAR CCM+, MATLAB/Simulink).
Surrogate Modeling & Automated Design Space Exploration (DSE): Build physics informed ML surrogates for key propulsion performance metrics (e.g., torque, BSFC/efficiency, thermal limits, emissions proxies, e drive efficiency maps) and integrate them with active learning data generation and multi objective optimization
MS or PHD in Computer Science, Computer Engineering, or Electrical Engineering
Skillset: Python programming (critical); Experience in AI/ML, preferably Generative AI (critical); familiarity with embedded software development lifecycle and systems engineering activities
• System architecture covering data sources (requirements, prior studies, PLM), tools (1D/3D solvers), and results storage (Lakehouse).
• Document parsing pipelines for requirements/specs/test plans; establish content normalization (Markdown/JSON).
• Agent workflows for: interpreting change requests, proposing simulation plans, generating run decks/templates, mesh/BC suggestions, and automated post processing.
• Chat + form based UI to request studies, generate inputs, and review outputs.
• Integration with Databricks (Lakehouse, MLflow, Model Serving) for versioning, observability, and scalable compute.
• Define target responses (e.g., torque map, efficiency map, pressure ratios, temperatures, emissions proxies), inputs (geometry/controls/operating points), and constraints.
• Data model and schema for simulation inputs/outputs; provenance and UQ metadata.
• Orchestrate solver sweeps (1D/CFD/FEA where applicable) to seed the dataset.
• Implement adaptive sampling/active learning to target high value points that reduce model error.
• Train candidate surrogates (e.g., GPR, XGBoost/TabNet, feedforward NNs, physics informed NNs).
• Cross validation, error budgets, calibration; uncertainty quantification and guardbanding.
• Integrate surrogates with DSE (e.g., Bayesian Optimization, NSGA II) to target objectives (efficiency/BSFC, mass, cost, thermal margins) under constraints (emissions/temperature/packaging).
• Optional coupling to MDAO toolchains (e.g., ModelCenter/HEEDS/Simcenter).
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About Lorven technologies

Sourced by ZipRecruiter

Lorven Technologies, headquartered in Plainsboro, New Jersey, United States, is a reputable company in the technology industry, specializing in providing effective IT solutions and consulting services. The company's official website, lorventech.com, offers comprehensive insights into its offerings which include but are not limited to software development, IT consulting, project management, and business analysis. Since its inception, Lorven Technologies has been committed to ensuring efficiency and reliability in delivering IT services to its global clientele, establishing itself as a trusted name in the industry.

Industry

It services

Company size

51 - 200 Employees

Headquarters location

Plainsboro, NJ, US

Year founded

2001

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